Systems, Methods, and Devices for Head Pose Determination

1. A non-transitory computer readable medium comprising instructions that when executed by the at least one processor cause the at least one processor to: obtain sensor data corresponding to a head and at least a portion of the body of a human subject; determine an estimate of a body pose using the obtained sensor data; generate a first rendering of at least the human subject's head using the obtained sensor data; generate at least one head pose data set with a generative model based on the estimated body pose, generate at least one second rendering using the at least one head pose dataset; and determine at least one likeness factor between the first and the at least one second rendering.

2. The computer readable medium of claim 1, wherein to determine the estimate of the body pose using the obtained sensor data comprises to use one or more of a machine learning technique, a neural network, a trajectory the human subject is on, historic pose data of the human subject, or a database or knowledge of human subject poses, an environment context the human subject and/or other actors is in.

3. The computer readable medium of claim 1, wherein the body pose is a 3D body pose.

4. The computer readable medium of claim 1, wherein the at least one head pose data set comprises a plurality of head pose data sets, and wherein to generate the at least one respective second rendering comprises to generate a plurality of second renderings respectively from using the plurality of the head pose data sets, and wherein to determine the at least one likeness factor comprises to determine a likeness factor for each of the plurality of second renderings.

5. The computer readable medium of claim 4, wherein the instructions when executed, further cause the at least one processor to further determine one of the plurality of second renderings to be closest to the first rendering using the respective likeness factor.

6. The computer readable medium of claim 1, wherein to determine which one of the plurality of second renderings is closest to the first rendering comprises to determine which one of the plurality of second renderings is closest to the first rendering using a likelihood function.

7. The computer readable medium of claim 1, wherein the instructions when executed, further cause the at least one processor to: select the head pose data set corresponding to the second rendering determined closest to the first rendering.

8. The computer readable medium of claim 1, wherein to generate the head pose data set comprises to generate a random sampling of head pose data.

9. The computer readable medium of claim 1, wherein to generate the first rendering comprises to generate the first rendering from a viewpoint corresponding to a sensor origin viewpoint of the obtained sensor data.

10. The computer readable medium of claim 1, wherein the at least one processor renders the first and second renderings in a same render space.

11. The computer readable medium of claim 1, wherein one or more facial features of human subject's head in the obtained sensor data are concealed or occluded.

12. The computer readable medium of claim 1, wherein the generative model comprises a conditional probability distribution of head pose data sets.

13. The computer readable medium of claim 12, wherein the conditional probability distribution of head pose data sets comprises a conditional probability distribution of one or more head pose parameters.

14. The computer readable medium of claim 12, wherein the conditional probability distribution of head pose data sets comprises a conditional probability distribution of observed head-pose data sets.

15. The computer readable medium of claim 1, wherein the obtained sensor data comprises video data.

16. The computer readable medium of claim 15, wherein determining an estimate of the body pose comprises determining a body pose for each of a plurality of sequential frames from the video data, and wherein generating the at least one head pose data sets comprising successively applying each of the estimated 3D body poses and applying a corresponding previously generated head pose data to the generative model.

17. A head pose apparatus comprising: an interface, coupled to at least one sensor, to receive sensor data from the at least one sensor, the sensor data corresponding to a head and at least a portion of the body of a human subject; a head pose estimator comprising: at least one processor; and a non-transitory computer readable medium comprising instructions that when executed by the at least one processor cause the at least one processor to: determine an estimate of a body pose using the obtained sensor data; generate a first rendering of at least the human subject's head using the obtained sensor data; generate at least one head pose data set with a generative model based on the estimated body pose, generate at least one second rendering using the at least one head pose dataset; and determine at least one likeness factor between the first and the at least one second rendering.

18. The head pose apparatus of claim 17, wherein the at least one head pose data set comprises a plurality of head pose data sets, and wherein to generate the at least one respective second rendering comprises to generate a plurality of second renderings respectively from using the plurality of the head pose data sets, and wherein to determine the at least one likeness factor comprises to determine a likeness factor for each of the plurality of second renderings.

19. The head pose apparatus of claim 17, wherein the instructions when executed, further cause the at least one processor to further determine one of the plurality of second renderings to be closest to the first rendering using the respective likeness factor.

20. A head pose estimator comprising: means for obtaining sensor data corresponding to a head and at least a portion of the body of a human subject; means for determining an estimate of a body pose using the obtained sensor data; means for generating a first rendering of at least the human subject's head using the obtained sensor data; means for generating head pose data; means for generating at least one second rendering from the head pose data, and means for selecting one of the plurality of the second renderings that is closest to the first rendering.